Gastric cancer is one of the common malignant tumours in clinical practice with poor prognosis and high mortality. Icariside II is a single compound extracted from the traditional Chinese medicine Epimedium brevicornu Maxim, and it is also the main active ingredient of Epimedium brevicornu Maxim that exerts pharmacological effects. Studies have shown that Icariside II has anti-tumour activity, but its mechanism of action on gastric cancer cells is unclear. This study aims to analyze the impact of Icariside II on gastric cancer cells as well as on xenograft tumor models of gastric cancer, and to examine the potential molecular regulatory pathways. GES-1, a normal gastric cell line, and gastric cancer cell lines AGS and MGC803 were cultured to investigate the cytotoxic effects of Icariside II using the methylthiazolyldiphenyl-tetrazolium (MTT). Flow cytometry (FCM) was employed to measure the impact of Icariside II on the apoptosis levels of gastric cancer cells, while western blot analysis was used to examine the expression of apoptosis-related proteins and the Wnt/β-catenin signaling pathway. Subsequently, a xenograft tumor model was established and treated with Icariside II to observe changes in tumor volume and weight in the model mice. Finally, alterations in the expression of the Wnt/β-catenin signaling pathway were assessed through immunofluorescence (IF) and immunohistochemistry (IHC). The results showed that Icariside II had faint significant toxic effect on GES-1 cells, and was able to inhibit the proliferative activity and promote apoptosis of the gastric cancer cells. Moreover, Icariside II was able to inhibit the growth of gastric cancer in nude mice subcutaneous transplantation tumor. In addition, both in vivo and in vitro results indicated that Icariside II inhibited the activation of the Wnt/β-catenin signaling pathway. Icariside II inhibited tumorigenicity of gastric cancer by suppressing the Wnt/β-catenin signaling.

Cerebral infarction is a predominant cause of global disability and mortality, characterized by pathogenesis that includes vascular stenosis, thrombosis, ischemic necrosis, and neuroinflammation. Despite progress in medical science, effective treatments for cerebral infarction are still constrained, prompting the investigation of alternative therapeutic strategies.

The objective of this review is to assess the efficacy of Traditional Chinese Medicine (TCM) as a treatment for cerebral infarction, emphasizing its mechanisms of action, effectiveness, and clinical relevance.

An extensive review of the existing literature regarding the role of TCM in the management of cerebral infarction, encompassing investigations on specific remedies, Chinese medicinal formulations, and contemporary advancements in preparation methodologies.

This review analyzes diverse TCM remedies recognized for their antioxidant, anti-inflammatory, and neuroprotective properties. Furthermore, it examines the synergistic effects of Chinese medicine formulations in modulating inflammation, enhancing blood circulation, and facilitating neural repair. Contemporary technological advancements that improve the accuracy and efficacy of Chinese medicine are also taken into account.

TCM has shown considerable promise in tackling the complex aspects of cerebral infarction. Specific remedies and formulations have demonstrated potential in modulating inflammatory responses, enhancing cerebral blood flow, and promoting neural repair mechanisms. Contemporary formulations have enhanced these effects, facilitating more precise and effective treatment.

While TCM presents a promising multi-faceted and multi-tiered strategy for addressing cerebral infarction, obstacles such as elucidating mechanisms and achieving standardization must be addressed. Continued research and clinical trials are crucial to fully exploit the therapeutic potential of TCM in the management of cerebral infarction.

Chromatographic separation plays an essential role in medicinal research, especially for complex natural products such as traditional Chinese medicine (TCM), where selecting a suitable stationary phase is of primary importance and requires significant effort. Existing stationary phase screening (SPS) methods often necessitate inflexible and expensive instrumentation or a prolonged screening period. Despite this, efforts are mostly focused on stationary phases with significantly different properties, while those with subtle differences, e.g., various C18 stationary phases, are often overlooked, which can result in remarkably different chromatographic layouts, especially in pursuing optimum selectivity of target active components in TCM analysis. Herein, we report an efficient, low-cost, and easy-to-prototype parallel array microfluidic column liquid chromatography (palmLC) platform for SPS based on batch-prepared capillary columns and a multichannel capillary microfluidic assembly. In comparison with a standard single-column system, the developed palmLC system maintained a nondegradable chromatographic performance in terms of efficiency (5110 vs 5150 plates) and resolution (2.77 vs 3.39), ensuring reliable screening results while achieving a 600% increase in screening efficiency. In the case studies of Panax notoginseng and Gastrodia elata, among the six C18 phases screened, the C18 phase with the best separation performance was successfully identified. Finally, in SPS for Polygala tenuifolia separation, along the chromatograms, different C18 phases presented individual optimum resolutions for certain medicinal components, indicating that the six-in-one-shot palmLC strategy can effectively provide a panoramic display of the medicinal material, suggesting it is a useful tool for high definition quality control and profiling in TCM analysis.

Symptom phenotypes are crucial for diagnosing and treating various disease conditions. However, the diversity of symptom terminologies poses a significant challenge to analyzing and sharing of symptom-related medical data, particularly in the field of traditional Chinese medicine (TCM). This study aims to construct an Integrated Symptom Phenotype Ontology (ISPO) to support data mining of Chinese electronic medical records (EMRs) and real-world studies in the TCM field.We manually annotated and extracted symptom terms from 21 classical TCM textbooks and 78,696 inpatient EMRs, and integrated them with five publicly available symptom-related biomedical vocabularies. Through a human-machine collaborative approach for terminology editing and ontology development, including term screening, semantic mapping, and concept classification, we constructed a high-quality symptom ontology that integrates both TCM and Western medical terminology.ISPO provides 3,147 concepts, 23,475 terms, and 23,363 hierarchical relationships. Compared with international symptom-related ontologies such as the Symptom Ontology, ISPO offers significant improvements in the number of terms and synonymous relationships. Furthermore, evaluation across three independent curated clinical datasets demonstrated that ISPO achieved over 90% coverage of symptom terms, highlighting its strong clinical usability and completeness.ISPO represents the first clinical ontology globally dedicated to the systematic representation of symptoms. It integrates symptom terminologies from historical and contemporary sources, encompassing both TCM and Western medicine, thereby enhancing semantic interoperability across heterogeneous medical data sources and clinical decision support systems in TCM.

Objectives: Jasminoidin (JA) and ursodeoxycholic acid (UA) have been shown to exert synergistic effects on cerebral ischemia (CI) therapy, but the underlying mechanisms remain to be elucidated. Objective: To elucidate the synergistic mechanisms involved in the combined use of JA and UA (JU) for CI therapy using a driver-induced modular screening (DiMS) strategy. Methods: Network proximity and topology-based approaches were used to identify synergistic modules and driver genes from an anti-ischemic microarray dataset (ArrayExpress, E-TABM-662). A middle cerebral artery occlusion/reperfusion (MCAO/R) model was established in 30 Sprague Dawley rats, divided into sham, vehicle, JA (25 mg/mL), UA (7 mg/mL), and JU (JA:UA = 1:1) groups. After 90 minutes of ischemia, infarct volume and neurological deficit scores were evaluated. Western blotting was performed 24 h after administration to validate key protein changes. Results: Six, eleven, and four drug-responsive On_modules were identified for JA, UA, and JU, respectively. Three synergistic modules (Sy-modules, JU-Mod-7, 8, and 10) and 12 driver genes (e.g., NRF1, FN1, CUL3) were identified, mainly involving the PI3K-Akt and MAPK pathways and regulation of the actin cytoskeleton. JA and UA synergistically reduced infarct volume and neurological deficit score (2.5, p < 0.05) in MCAO/R rats. In vivo studies demonstrated that JU suppressed the expression of CUL3, FN1, and ITGA4, while it increased that of NRF1. Conclusions: JU acts synergistically on CI-reperfusion injury by regulating FN1, CUL3, ITGA4, and NRF1 and inducing the PI3K-Akt, MAPK, and actin cytoskeleton pathways. DiMS provides a new approach to uncover mechanisms of combination therapies.

Bufalin is a potent bioactive compound extracted from the venom of toads such as Bufo gargarizans. It has rich pharmacological effects, and its traditional applications mainly include anti-cancer, anti-inflammatory and analgesic, especially in cancer treatment, which has been a hot topic of research. Prior research has suggested that bufalin may have anti-tumor angiogenic effects. However, the efficacy and mechanism of bufalin inhibiting hepatocellular carcinoma (HCC) angiogenesis have yet to be further investigated.

An extensive detailed strategy via network pharmacology, proteomics, histopathological analysis, molecular docking, in vitro experiments, and in vivo magnetic resonance imaging (MRI) examinations were adopted to investigate the efficacy and mechanisms of bufalin against HCC angiogenesis.

Micro-vessel density (MVD) and intravoxel incoherent motion (IVIM) perfusion-related parameters based on magnetic resonance diffusion-weighted imaging were used to identify the effect of bufalin against HCC angiogenesis. Potential bufalin and HCC targets were gathered from appropriate databases. The STRING database was used to construct the target protein interaction networks. The "clusterprofiler" package (version 4.2.2) in R was applied to conduct the target-related Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) analysis. Network pharmacology and proteomics were integrated to identify key targets and pathways related to bufalin against HCC angiogenesis. Molecular docking and Western Blot were utilized to validate the findings.

Analysis through IVIM and MVD showed that bufalin could inhibit HCC angiogenesis in nude mice models. A total of 159 common targets of bufalin and HCC were identified by network pharmacology. GO analysis revealed that these targets focused on multiple angiogenesis-related biological processes, including endothelial cell proliferation and migration, sprouting angiogenesis, and regulation of angiogenesis. The KEGG enrichment results suggested that bufalin could regulate multiple signaling pathways to inhibit HCC angiogenesis, including VEGF, MAPK, PI3K-Akt, mTOR, and HIF-1 signaling pathways. MAPK1, MAPK14, PRKCA, EIF4E, and APEX1 might be critical targets in regulating the above pathways. The molecular docking and Western blot analysis verified the effects of bufalin on target proteins.

This study demonstrated that bufalin might inhibit HCC angiogenesis by regulating multiple targets and pathways. These findings offer theoretical insights and experimental foundations for the clinical application and commercial development of bufalin in the treatment of HCC.

Traditional Chinese medicine is a complex medical system characterized by multiple metabolites, targets, and pathways, known for its low drug resistance and significant efficacy. However, challenges persist within Traditional Chinese medicine, including difficulties in assessing the quality of Botanical drugs, reliance on experiential knowledge for disease diagnosis and treatment, and a lack of clarity regarding the pharmacological mechanisms of Traditional Chinese medicine. The advancement of digital intelligence technology is driving a shift towards precision medicine within the Traditional Chinese medicine model. This transition propels Traditional Chinese medicine into an era of precision, intelligence, and digitalization. This paper introduces standard digital intelligence technologies and explores the application of digital intelligence technologies in quality control and evaluation of Traditional Chinese medicine, studies the research status of digital intelligence technologies in assisting diagnosis, treatment and prevention of diseases, and further promotes the application and development of digital intelligence technologies in the field of Traditional Chinese medicine.

Traditional Chinese medicine (TCM) exerts integrative effects on complex diseases owing to the characteristics of multiple components with multiple targets. However, the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians, which has been a major challenge in the global acceptance and application of TCM. Therefore, a standardized TCM prescription system needs to be explored to promote its clinical application. In this study, we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation. We tested its efficacy against intracerebral hemorrhage (ICH). First, the top 100 ICH targets in the GeneCards database were screened according to their relevance scores. Then, SymMap and Traditional Chinese Medicine Systems Pharmacology (TCMSP) databases were applied to find out the target-related ingredients and ingredient-containing herbs, respectively. The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets. The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions. The absorbed components in the serum were detected. In a mouse model of ICH, the new prescription exerted multifaceted effects, including improved neurological function, as well as attenuated neuronal damage, cell apoptosis, vascular leakage, and neuroinflammation. These effects matched well with the core pathological changes in ICH. The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise, multipronged, unbiased, and standardized TCM prescriptions for complex diseases. This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

Neuropathic pain (NP) is a type of chronic pain resulting from injury or dysfunction of the nerves or spinal cord. Previous studies have shown that the combination of ligustrazine (LGZ) and sinomenine (SIN) exerts a synergistic antinociceptive effect in peripheral and central NP models. On this basis, a comprehensive analgesic evaluation was performed in a chronic constriction injury (CCI)-induced NP model in rats. Sciatic nerve histopathological changes were observed, and 22 cytokines and chemokines levels were analyzed. We also combined network pharmacology and metabolomics to explore their molecular mechanisms. Results showed that the combination of LGZ and SIN significantly alleviated the pain-like behaviors in CCI rats in a time- and dose-dependent manner, demonstrating superior therapeutic effects compared to LGZ or SIN alone. It also improved pathological damage to sciatic nerves and regulated inflammatory cytokine levels. Network pharmacology identified shared and distinct pain-related targets for LGZ and SIN, while metabolomics revealed 54 differential metabolites in plasma, and 17 differential metabolites in CSF were associated with the combined intervention of LGZ and SIN. Finally, through an integrated analysis of the core targets and differential metabolites, tyrosine metabolism, phenylalanine metabolism, and arginine and proline metabolism were identified as potential key metabolic pathways underlying the therapeutic effects of LGZ and SIN in CCI treatment. In conclusion, our study provides evidence to support the clinical application of LGZ and SIN in the treatment of NP.

In the contemporary medical landscape, the burgeoning interest in natural therapies, particularly for managing gastrointestinal disorders, has brought traditional Chinese medicine (TCM) to the forefront. This article explains the core principles and clinical applications of TCM in treating these conditions, furthering the discourse through an examination of integrated TCM strategies, as demonstrated in the study by Zhou et al. While TCM has shown promising clinical outcomes, it encounters significant hurdles in standardization, mechanistic research, and clinical validation. Future investigations should aim to solidify the scientific underpinnings of TCM and expand its use in gastrointestinal disease management, striving for a seamless fusion of traditional and contemporary medical practices.

Identifying the active natural compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. Here, we proposed Meta-DEP, a Meta-paths-based Drug Efficacy Prediction based on drug-protein-disease heterogeneity network, where Meta-paths contain all the shortest paths between drug targets and disease-related proteins in the network and drug efficacy is measured by a predictive score according to drug disease network proximity. Experiments show that Meta-DEP performs better than traditional network topology analysis on drug-disease interaction prediction task. Further investigations demonstrate that the key targets identified by Meta-DEP for drug efficacy are consistent with clinical pharmacological evidence. To prove that Meta-DEP can be used to discover active natural compounds, we apply it to predict the relationship between the monomeric components of traditional Chinese medicine included in the TCMSP database and diseases. Results indicate that Meta-DEP can accurately predict most of the drug-disease pairs included in the TCMSP database. In addition, biological experiments are directly used to demonstrate that Meta-DEP can mined active compound from traditional Chinese medicine with integrating disease transcriptomic data. Overall, the model developed in this study provides new impetus for driving the natural compound into innovative lead molecule. Code and data are available at https://github.com/t9lex/Meta-DEP .

Although acknowledged as an important complement to modern medicine, the utility of natural medicine (NM) remains under-exploited. We aimed to develop a novel data-driven approach for natural medicine discovery.

GWAS summary statistics of disease (Alzheimer's disease, i.e., AD, for the case study) and quantitative trait loci were collected from public sources. The ranking of disease-gene associations was established using summary-based Mendelian randomization. The comprehensive hierarchical relationships among ingredients, natural products, and target genes were compiled from the BATMAN-TCM v2.0 database. Based on the ranking of disease-gene associations and the comprehensive hierarchical relationships among ingredients, natural products, and target genes, we prioritized NM ingredients as potential candidates for AD management and examined the efficacy for AD prevention using rat AD models.

We developed a non-trivial transparent data-driven framework for systems genetics-based NM discovery. Among the 139 prioritized candidates for AD management, we demonstrated the efficacy of Dang Gui (Angelicae Sinensis Radix, ASR) and Dang Shen (Codonopsis Pilosula, CP) for AD prevention using rat models. Mechanistically, we showed that ASR may prevent AD-related damage through protection of neural cells, as well as inhibition of microglia, angiogenesis, inflammation, and extracellular matrices.

Our method holds potential for the development of new strategies of complementary medicine for disease treatment and prevention, especially for complex conditions involving a number of genes.

Current treatments for ulcerative colitis (UC) remain limited, highlighting the need for novel therapeutic strategies. Trilobatin (TLB), a naturally derived food additive, exhibits potential anti-inflammatory properties. In this study, a dextran sulfate sodium (DSS)-induced animal model is used to investigate the effects of TLB on UC. It is found TLB significantly alleviates DSS-induced UC in mice, as evidenced by a reduction in the disease activity index, an increase in colon length, improvement in histopathological lesions. Furthermore, TLB treatment results in a decrease in proinflammatory cytokines and an increase in anti-inflammatory cytokines. TLB mitigates UC by modulating the intestinal microbiota, particularly Akkermansia, which enhances tryptophan metabolism and upregulates the production of xanthurenic acid (XANA). To confirm the role of TLB-induced microbiota changes, experiments are performed with pseudogerm-free mice and fecal transplantation. It is also identified XANA as a key metabolite that mediates TLB's protective effects. Both TLB and XANA markedly activate the aromatic hydrocarbon receptor (AhR). Administration of an AhR antagonist abrogates their protective effects, thereby confirming the involvement of AhR in the underlying mechanism. In conclusion, the study reveals a novel mechanism through which TLB alleviates UC by correcting microbiota imbalances, regulating tryptophan metabolism, enhancing XANA production, and activating AhR.

Efficient virtual screening methods can expedite drug discovery and facilitate the development of innovative therapeutics. This study presents a novel transfer learning model based on network target theory, integrating deep learning techniques with diverse biological molecular networks to predict drug-disease interactions. By incorporating network techniques that leverage vast existing knowledge, the approach enables the extraction of more precise and informative drug features, resulting in the identification of 88,161 drug-disease interactions involving 7,940 drugs and 2,986 diseases. Furthermore, this model effectively addresses the challenge of balancing large-scale positive and negative samples, leading to improved performance across various evaluation metrics such as an Area under curve (AUC) of 0.9298 and an F1 score of 0.6316. Moreover, the algorithm accurately predicts drug combinations and achieves an F1 score of 0.7746 after fine-tuning. Additionally, it identifies two previously unexplored synergistic drug combinations for distinct cancer types in disease-specific biological network environments. These findings are further validated through in vitro cytotoxicity assays, demonstrating the potential of the model to enhance drug development and identify effective treatment regimens for specific diseases.

The urgent need to identify pathways that can mitigate myocardial ischemia-reperfusion injury (MIRI) has become a central focus in cardiovascular treatment. Chinese herbal medicine (CHM), renowned for its multi-component, multi-channel, and multi-target therapeutic properties, holds significant promise in the management of MIRI. Mitochondria, as pivotal players in MIRI, have been shown to be effectively modulated by CHM through various mechanisms. The objective of this narrative review is to underscore the critical role of mitochondria in MIRI and to provide an up-to-date overview of the latest research advancements in utilizing CHM to treat MIRI by targeting mitochondrial morphology and function.

The PubMed and the China National Knowledge Infrastructure (CNKI) databases were searched using keywords related to MIRI. Relevant English-language articles published from January 2019 to July 2024 were included in this narrative review.

Mitochondria are intimately linked to MIRI. The mechanisms involve the regulation of mitochondrial biogenesis and energy metabolism, the functionality of the mitochondrial respiratory chain, resistance to oxidative stress-induced damage, the maintenance of mitochondrial homeostasis, the modulation of calcium ion homeostasis, the preservation of mitochondrial membrane potential, the opening of adenosine triphosphate (ATP)-sensitive potassium channels, and the effective control over the opening of the mitochondrial permeability transition pore, all of which contribute to the balance between autophagy and apoptosis in cardiomyocytes. Various effective monomers of CHM, extracts of CHM, compounds, and proprietary Chinese medicine have demonstrated promising therapeutic potential in basic research, among them, tonic and blood-activating CHMs account for the largest proportion.

The prospect of CHM targeting mitochondria for the treatment of MIRI is promising, yet it necessitates overcoming challenges such as low bioavailability and inadequate mechanistic research. By integrating traditional Chinese medicine theories with modern scientific technologies, it is imperative to delve deeper into and optimize the pharmacodynamics, pharmacokinetics, and clinical applications of these herbs.

Pseudostellaria heterophylla (Tài Zǐ Shēn, TZS) is a traditional Chinese medicine with spleen and qi benefits. Its immunomodulatory, anti-fatigue, anti-stress, and lipid metabolism regulation effects have been clinically confirmed, but its role in meibomian gland dysfunction (MGD) is still unclear.

This study aims to investigate the effect and mechanism of action of TZS in treating MGD.

Several therapeutic agents were used to predict MGD treatment using the "Disease-Syndrome-TCM" network mechanism. We then performed a network pharmacology analysis to identify possible targets and pathways for drug treatment of the disease. It was then validated by in vitro experiments. The animal models were taken and analyzed by slit lamp and stereo microscope. HE and ORO staining analysis were then performed. Next, the expressions of key protein indicators were tested by IF, and finally the metabolism of key substances such as lipids and ceramides were detected by SRS imaging.

The "Disease-Syndrome-TCM" network mechanism was used to predict several therapeutic agents for MGD treatment including TZS et al. Network pharmacology analysis revealed that the targets of active components in the total saponins of TZS (PHS) were significantly enriched in the pathways of PPAR and AMPK. Subsequently, seven targets of PHS were identified, which were enriched in signaling pathways associated with lipid metabolism and inflammation. Furthermore, in vivo experiments showed that PHS alleviated meibomian glands (MG) obstruction and atrophy induced by A939, a SCD1 inhibitor. PHS treatment significantly increased PPAR-γ proteins in MGs, contributing to the normal differentiation of acini. Additionally, PHS treatment resulted in a reduction in the number of K10-positive cells, which partially prevented keratinization and abnormal differentiation of acinar cells. TUNEL assay results indicated that PHS mitigated apoptosis in MGs. Detailed exploration using Raman spectroscopy imaging showed that PHS could enhance the expression of SCD1 protein and the unsaturation degree of fatty acids, which in turn downregulated SPT1 protein and endogenous ceramides de novo biosynthesis.

This study elucidated the effects of PHS in alleviating MGD and highlighted the pharmacological mechanisms involved, specifically the upregulation of SCD1 and inhibition of de novo ceramides biosynthesis. These findings provided a research basis for advancing its clinical application in MGD treatment.

Previous study has demonstrated lancao decoction (LC), a traditional Chinese medicine (TCM) fomula and recorded in "Huangdineijing", has a therapeutic effect on cognitive impairment (early clinical manifestations of alzheimer's disease (AD), which suggests that LC may have potential therapeutic advantages for AD. Whether LC has the therapeutic effect on AD and its potential mechanisms were still further indicated.

In this study, we aimed to uncover the potential advantage and neuronal mechanisms of LC in the treatment of AD in APP/PS1 mice in the hippocampus.

We chose APP/PS1 mice to combing with behavioral tests including morris water maze (MWM) or y-maze to determine the role of LC in the therapeutic actions of AD. Network pharmacology was used to screen potential targets and pathways involving in LC's treatments of AD. Western blot was used to detect the phosphorylated expressions of proteins in hippocampus in APP/PS1 mice in the hippocampus. Pharmacological interventions were used to elucidate the relationship between the role of LC in the treatment of AD and the pathway, as well as the upstream and downstream interactions with neuronal activities.

According to our previous LC effective dose (2.5 g/kg), the dose was also able to significantly reduce the latency to the platform, and significantly increase the number of crossing times and time spend in the target quadrant in APP/PS1 mice in MWM, which was consistent with donepezil (DON) after 14 days chronic treatments. Network pharmacology showed that PI3K/AKT and MAPK pathways were closely associated with LC's treatments of AD, and protein autophosphorylation played a role in this process. The phosphorylated expressions of PI3K and AKT were obviously reduced in APP/PS1 mice in the hippocampus, which were both reversed by LC or DON. The phosphorylated expressions of MAPK including P38, JNK and ERK were also significantly reduced in APP/PS1 mice hippocampus, but only the phosphorylated expression of ERK was reversed by LC or DON. Inhibiting the activities of PI3K/AKT pathway by LY294002 blocked LC's improvement of behavioral deficits in APP/PS1 mice, including reducing latency to platform and increasing the number of crossings time in MWM in APP/PS1 mice, which also blunted LC's up-regulated phosphorylated expressions of PI3K, AKT and ERK in the hippocampus. Moreover, suppressing the activities of ERK by PD98059 also blocked LC's improvement of AD-related behavioral deficits including decreasing latency to new arm and increasing time in new arm in y-maze test, which also inhibited LC's enhancement of synaptic proteins (PSD95 and synapsin1) in the hippocampus and the number of EGR1-positive cells in the hippocampal dentate gyrus (DG).

Take together, our study revealed that LC had the therapeutic effects on AD by activating the PI3K/AKT pathway to enhance ERK activity and further strengthened neuronal activities in the hippocampus.

Ginseng has historically been utilized as a conventional herbal remedy and dietary supplement to enhance physical stamina and alleviate fatigue. The primary active component of Ginseng, Ginsenoside Rg3 (GS-Rg3), possesses diverse pharmacological properties including immune modulation and anti-inflammatory effects. Furthermore, GS-Rg3 has demonstrated efficacy in mitigating tissue and organ damage associated with metabolic disorders such as hypertension, hyperglycemia, and hyperlipidemia. Nevertheless, its potential impact on high-altitude cardiac injury (HACI) remains insufficiently explored.

The aim of this study was to examine the potential cardioprotective effects of Ginsenoside Rg3, and to investigate how Ginsenoside Rg3 preconditioning can enhance high-altitude cardiac injury by inhibiting the RhoA/ROCK pathway and ferroptosis in cardiac tissue. The findings of this study may contribute to the development of novel therapeutic strategies using traditional Chinese medicine for high-altitude cardiac injury, based on experimental evidence.

A hypobaric hypoxia chamber was employed to simulate hypobaric hypoxia conditions equivalent to an altitude of 6000 m. Through a randomization process, groups of six male mice were assigned to receive either saline, Ginsenoside Rg3 at doses of 15 mg/kg or 30 mg/kg, or lysophosphatidic acid (LPA) at 1 mg/kg. The impact of Ginsenoside Rg3 on high altitude-induced arrhythmias was evaluated using electrocardiography. Cardiac pathology sections stained with hematoxylin and eosin were evaluated for damage, with the extent of cardiomyocyte damage observed via transmission electron microscopy. The impact of Ginsenoside Rg3 on high-altitude cardiac injury was investigated through analysis of serum biomarkers for cardiac injury (CK-MB, BNP), inflammatory cytokines (TNF, IL-6, IL-1β), reactive oxygen species (ROS) and glutathione (GSH). The expression levels of hypoxia and hypoxia-related proteins in myocardial tissues from each experimental group were assessed using Western blot analysis. Following a review of the existing literature, the traditional regulatory mechanisms of ferroptosis were examined. Immunofluorescence staining of cardiac tissues and Western blotting techniques were utilized to investigate the impact of Ginsenoside Rg3 on cardiomyocyte ferroptosis through the RhoA/ROCK signaling pathway under conditions of hypobaric hypoxia exposure.

Pre-treatment with Ginsenoside Rg3 improved high altitude-induced arrhythmias, reduced cardiomyocyte damage, decreased cardiac injury biomarkers and inflammatory cytokines, and lowered the expression of hypoxia-related proteins in myocardial tissues. Both Western blotting and immunofluorescence staining of cardiac tissues demonstrated that exposure to high-altitude hypobaric hypoxia results in elevated expression of ferroptosis and proteins related to the RhoA/ROCK pathway. Experimental validation corroborated that the role of the RhoA/ROCK signaling pathway in mediating ferroptosis.

The findings of our study suggest that preconditioning with Ginsenoside Rg3 may attenuate cardiac injury caused by high-altitude hypobaric hypoxia exposure in mice by inhibiting ferroptosis through the suppression of the RhoA/ROCK signaling pathway. These findings contribute to the current knowledge of Ginsenoside Rg3 and high-altitude cardiac injury, suggesting that Ginsenoside Rg3 shows potential as a therapeutic agent for high-altitude cardiac injury.

The pathological progression from liver injury to fibrosis is a hallmark of liver disease, with no effective strategies to halt this transition. Ginsenoside Rg1 has demonstrated a range of hepatoprotective properties; however, systematic preclinical evidence supporting its therapeutic potential for liver injury and fibrosis remains limited. Purpose. This study evaluated the efficacy and underlying mechanisms of ginsenoside Rg1 in animal models of liver injury and fibrosis, and providing a basis for future clinical investigation.

A systematic review was conducted on preclinical studies published in PubMed, Web of Science, and Embase databases up to 1 August 2024, adhereing to rigorous quality standards. The methodological quality was assessed using SYRCLE's risk of bias tool. Meta-analysis and subgroup analysis were performed using Revman 5.4 software, while publication bias was evaluated through funnel plots and Egger's test in STATA 15.0 software. Additionally, a time-dose interval curve was utilized to assess the dose-response relationship and identify the effective dose of ginsenoside Rg1 for treating liver injury and fibrosis.

Twenty-four trials involving 423 animals were included. The findings indicated that ginsenoside Rg1 significantly improved liver function markers (ALT and AST), reduced pathological indicators associated with liver injury and fibrosis, and lowered liver fibrosis-related markers (α-SMA, HYP, and PCIII). Furthermore, it exhibited beneficial effects on mechanistic indicators of inflammation, oxidative stress, and apoptosis, compared to the control group (P < 0.05). Time-dose interval analysis revealed that the effective dose range of ginsenoside Rg1 was between 4 and 800 mg/kg/d.

Rg1 at a dose of 4-800 mg/kg/d mitigates the progression of liver injury to fibrosis via anti-inflammatory, antioxidative, and anti-apoptotic pathways.

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD 42024557878.

Air pollution is a leading contributor to the global disease burden. However, the complex nature of the chemicals to which humans are exposed through inhalation has obscured the identification of the key compounds responsible for diseases. Here, we develop a network topology-based framework to identify key toxic compounds in the airborne chemical exposome. Using cardiovascular diseases (CVDs) as a model disease, we found that toxic network modules of various compounds are closely linked to the modules of CVDs. The proximity of compound target modules to disease modules can indicate the extent of toxicity induced by the compounds. By integrating mass spectrometry-based external exposure concentrations and machine learning-predicted internal exposure concentrations, we established a comprehensive linkage connecting exposure to disease-related risk for the identification of toxic compounds. These findings were subsequently validated using exposure and disease data on the regional scale. This work provides an effective strategy for identifying key compounds within environmental exposomes and establishes a new paradigm for understanding the pathogenicity of air pollution.

Gout is a common type of arthritis marked by monosodium urate (MSU) crystal deposition in joints, triggering an inflammatory response. Qu-Shi-Xie-Zhuo (QSXZ), a traditional Chinese medicine (TCM) formula, has been clinically used for the treatment of gouty arthritis (GA).

The study sought to examine the impact of QSXZ on GA and to delve into the pharmacological mechanisms that underlie its effects.

The chemical constituents of QSXZ were analyzed through UPLC-MS. MSU-induced acute gouty arthritis (AGA) and subcutaneous (SC) air pouch models in mice were employed to evaluate the anti-inflammatory properties of QSXZ and its primary active compound, Cryptotanshinone (CTS). To investigate the therapeutic mechanisms of QSXZ, we used MS-based network pharmacology, transcriptomic analysis, molecular docking and multiscale bioassays.

Treatment of QSXZ revealed a significant reduction of inflammatory cell infiltration and the expression of pro-inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin -1β (IL-1β). Based on UPLC/MS/MS results, 49 components were considered the active ingredients of QSXZ. Network pharmacology analysis indicated that QSXZ regulates multiple inflammation-related pathways. Subsequent transcriptomic analysis showed that QSXZ regulates gene expression of S100A8 and S100A9. Our investigation observed an increased expression of S100A8 and S100A9 in monocytes derived from gout patients. Molecular docking and molecular dynamics simulation analysis revealed the binding pattern and interaction between QSXZ active compound CTS and S100A8/A9, and subsequent surface plasmon resonance (SPR) and cell thermal shift assay (CETSA) experiments verified the direct interaction between them. To investigate the mechanisms of action, we conducted RT-PCR, Western blotting, immunohistochemistry, flow cytometry, and measured the inflammatory response. Our findings highlight the pathogenic role of S100A8/A9 mediated TLR4-NLRP3 axis in gout and review outstanding therapeutic effects of QSXZ and its primary active compound CTS on MSU-induced experimental models.

In summary, this study substantiates the therapeutic potential of QSXZ and its primary active compound CTS, as promising alternative treatments for GA. Our findings provide valuable insight into the critical pharmacological mechanism of QSXZ in regulating inflammation, highlighting its potential therapeutic effects in GA management.

This review aims at evaluating the role and potential applications of network analysis methods in the medicinal substances of traditional Chinese medicine (TCM), theories of TCM compatibility, properties of herbs, and TCM syndromes.

Literature was retrieved from databases, such as CNKI, PubMed, and Web of Science, using keywords, including "network analysis," "network biology," "network pharmacology," and "network medicine." The extracted literature included the biological network construction (including ingredient-target and target-disease relations), analysis of network topology characteristics (including node degree, clustering coefficient, and path length), network modularization analysis, functional annotation and so on. These studies were categorized and organized based on their research methods, application domains, and other relevant characteristics.

Network analysis algorithms, such as network distance, random walk, matrix factorization, graph embedding, and graph neural networks, are widely applied in fields related to the properties, compatibility, and mechanisms of TCM. They effectively reflect the interactive relations within the complex systems of TCM and elucidate and clarify theories, such as the effective substances, the principles of TCM compatibility, the TCM syndromes, and the properties of TCM.

The network analysis method is a powerful mathematical and computational tool that reveals the structure, dynamics, and functions of complex systems by analyzing the elements and their relations. This approach has effectively promoted the modernization of TCM, providing essential theoretical and practical tools for personalized treatment and scientific research on TCM. It also offers a significant methodological framework for the modernization and internationalization of TCM.

Evaluating the practical utility of endangered plant species is crucial for their conservation. Nevertheless, numerous endangered plants, including Sinocalycanthus chinensis, lack historical usage data, leading to a paucity of guidance in traditional pharmacological research. This gap impedes their development and potential utilization. Ultra-high-performance liquid chromatography and Orbitrap high-resolution mass spectrometry were employed to analyze the S. chinensis leaves collected at different harvesting times. Then, the metabolites were automatically annotated by a self-built R script in conjunction with characteristic fragment ions, neutral loss filtering, and feature-based molecular networking. By integrating metabolomics with network medicine analysis, the potential usage and optimal harvest times for S. chinensis were unlocked. A total of 305 metabolites were identified, with 66.8% annotated by self-built R script. A progressive increase in metabolite disparities was observed from May to August, followed by a relatively minor distinction from August to October. Notably diverse metabolites were detected in S. chinensis harvested during different periods, implying potential variations in efficacy. Network medicine analysis indicated possible therapeutic implications of S. chinensis for lung cancer, diabetes, bladder cancer, and Alzheimer's disease. Samples collected in May and September demonstrated exceptional efficacy. Harvesting was strategically conducted during these months based on variations in sample characteristics and metabolite content, tailored to their intended applications for dietary or medicinal purposes. This study developed an efficient methodology for investigating metabolites and exploring the potential applications of S. chinensis in food and herbal medicine. Consequently, it provides technical support for the sustainable conservation of endangered plants with limited clinical application experience.

As a representative active ingredient of traditional Chinese medicine (TCM) and a clinically approved anticancer drug, elemene (ELE) exhibits exciting potential in the antitumor field; however, appropriate drug formulations still need to be explored for specific diseases such as postoperative cancer recurrence and metastasis. Herein, we report an ELE hydrogel with controlled drug release kinetics that can allow ELE to maintain effective concentrations at local lesion sites for extended periods to enhance the bioavailability of ELE. Concretely, dopamine-conjugated hyaluronic acid is synthesized and utilized to prepare ELE nanodrug-embedded hydrogels. In a model of postoperative breast cancer recurrence and metastasis, the ELE hydrogel demonstrates a 96% inhibition rate of recurrence; in contrast, the free ELE nanodrug shows only a 65.5% inhibition rate of recurrence. Importantly, the ELE hydrogel markedly stimulates a potent antitumor immune response in the microenvironment of cancer lesions, increasing antitumor immune cells such as CD8+ T cells, CD4+ T cells, and M1-type macrophages, as well as elevating antitumor cytokines including TNF-α, IFN-γ, and IL-6. Overall, this study not only advances the field of TCM but also highlights the transformative impact of controlled-release hydrogels in improving antitumor therapy.

To systematically evaluate the effectiveness of the combined Needle Knife Therapy (NKT) and Chinese Herbal Medicine (CHM) treatment for knee osteoarthritis (KOA) and to provide clinical evidence supporting its application in managing the condition.

Relevant articles were retrieved from PubMed, Medline, Embase, Wanfang, and China National Knowledge Network (CNKI) from the inception of the databases up to February 18, 2023. Randomized controlled trials (RCTs) on the efficacy of NKT combined with CHM were appraised for inclusion. The meta-analysis was conducted using RevMan 5.3 and was registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) (202470051).

A total of 11 RCTs involving 880 patients were included. The meta-analysis showed that the combined therapy was superior to NKT alone in the treatment of KOA [relative risk (RR) = 1.09; 95% confidence interval (CI): (1.03, 1.14); P = 0.002]. The combined therapy showed a significant reduction in the Visual Analog Scale (VAS) score [RR = -0.98; 95% CI: -1.12, -0.84; P < 0.00001] and symptom scores [RR = -1.75; 95% CI: (-1.87, -1.63); P < 0.00001] compared to single NT therapy. There was no significant difference in the Traditional Chinese Medicine (TCM) syndrome scores between the two groups [RR = -0.23; 95% CI: (-0.56, 0.10); P = 0.18]. Furthermore, we observed a marked increase in lysholmy scores in the combination group than in the control group [RR = -1.04; 95% CI: (-1.31, -0.77); P < 0.00001].

The combination of needle-knife therapy and Chinese herbal medicine exhibits promising clinical efficacy in the treatment of KOA.

The drug discovery pipelines require enormous time and cost, albeit their infamously high risk of failures. Reducing such risk has therefore been the utmost goal in the process. Recently, natural products (NPs) in traditional oriental medicine (TOM) have come into the spotlight for their efficacy and safety supported throughout the history. Not only that, with the ever-increasing repository of various biological datasets, many data-driven in silico approaches have also been extensively studied for better efficient search and testing. However, TOM-based datasets lack information on recently prevalent diseases, while experimental datasets are prone to provide target spaces that are too large. Adequate combination of both approaches can therefore fill in each other's blanks. In this study, we introduce NaCTR, an in silico discovery pipeline that achieves such integration to suggest NPs-derived drug candidates for a given disease. First, phenotypes and disease genes for the disease are identified in literature and public databases. Secondly, a pool of potentially therapeutic NPs are identified based on both TOM-based phenotype records and compound-gene interaction datasets. Lastly, the compounds contained in the NPs are further screened for toxicity and pharmacokinetic properties. We use the Parkinson's disease as the case study to test the NaCTR pipeline. Through the pipeline, we propose glutathione and four other compounds as novel drug candidates. We further highlight the finding with literature support. As the first to effectively combine data from ancient and recent repositories, the NaCTR pipeline can be a novel pipeline that can be applied successfully to any other diseases.

Imperata cylindrica Beauv.var. major (Nees) C.E.Hubb., commonly known as BaiMaoGen (BMG), a medicinal and edible traditional Chinese medicinal (TCM) herb commonly used in health supplements, has been observed to offer protective effects against gastrointestinal disorders. However, the specific bioactive compounds and their molecular mechanisms have not been fully elucidated. This study employed ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) and systematic network pharmacology to analyze and identify the key active components and their interactions with biological targets. Thirty-six main active compounds, including 3,4-dihydroxybenzoic acid and p-hydroxybenzoic acid, were identified and analyzed for their interaction with key protein targets using molecular docking and dynamic simulations. This combined approach highlighted the therapeutic pathways involved, particularly the PI3K/AKT signaling pathways, providing new insights into the molecular basis of BMG's gastroprotective effects. Our findings suggested that BMG's complex multi-target action can potentially be harnessed to develop effective treatments for gastrointestinal toxicity.

It has been widely recognized that technologies evolve with recombinant inventions. However, it remains unknown whether technologies developed using different approaches would exhibit different features during evolution. In particular, would technologies developed mainly based on accumulated experience in practices-formulas of traditional Chinese medicine (TCM) are typical examples of such technologies-have similar evolution features found in modern technologies? This study applied network science to explore the evolution of TCM from the perspective of recombinant inventions based on 59,063 TCM formulas documented over the last two thousand years, with each formula being a combination of components that are mostly herbs. Our results show that similar to modern technological systems, the TCM component networks maintained the core-periphery structures during evolution, and the (weighted) degrees of components followed heavy-tailed distributions. Moreover, simple tuples, which are frequently used combinations of TCM components, serve as building blocks for complex ones. A significant difference with modern technological systems is that the TCM core components were quite stable, while substitutions of core components are frequently observed in modern technological systems, leading to new technological trajectories. TCM comprises ancient knowledge and wisdom. This research provides insight into how it will be like in the future and what is important for its future.

To investigate the characteristics of clinical trials on traditional Chinese medicine (TCM) or natural medicines for treating endometriosis, aiming to inform future clinical practice and the development of new effective drugs.

The global clinical trial registration platform was searched to identify clinical trials investigating the efficacy of TCM/natural medicine in treating endometriosis. Relevant trials were selected based on stringent inclusion and exclusion criteria. Data entry was performed using Microsoft Excel, while data analysis was conducted using SPSS version 23.

The study encompassed 57 trials, of which ClinicalTrials.gov accounted for 18, ChiCTR for 3, ICRP for 15, and ChiDTR for 21 trials. The number of registrations showed a significant positive correlation with the years. Of the 57 clinical trials, 87.7% were randomized, 63.2% were blinded, 78.9% followed a parallel intervention model, and 56.1% had a sample size below 100. Regarding trial phases, 45.6% of clinical trials did not specify a phase, while Phase 3 and Phase 4 clinical trials accounted for 17.5%. Nine clinical trials involved drugs that are already on the market, including six Chinese patent medicines: Sanjie Zhentong Capsules, Honghua Ruyi Pills, Huayu Sanjie Enema Liquid, Kuntai Capsules, Wenjing Tang, and Xuefu Zhuyu Capsules. Outside China, Iran has the highest number of registrations for natural medicine treatments for endometriosis, with curcumin being the most registered natural medicine.

The analysis reveals that clinical trials on TCM and natural remedies for endometriosis often utilize randomization; however, substantial deficiencies remain in blinding and sample size adequacy. These findings suggest that, despite growing interest in TCM and natural remedies, further methodological improvements are necessary to enhance the credibility of future studies. This research highlights the importance of rigorously designed clinical trials in verifying the safety and efficacy of these alternative therapies, which may influence future therapeutic approaches for managing endometriosis.

Acute lung injury (ALI) is a respiratory disease characterized by pulmonary inflammation and increased microvascular permeability, resulting in significant mortality and a lack of effective pharmacological treatment. Huangqin Qingfei Decoction (HQQFD), a Traditional Chinese Medicine (TCM) prescription known for its heat-clearing and detoxifying properties, has shown efficacy in treating ALI. However, the underlying mechanisms of HQQFD to against ALI remain to be elucidated.

This study aims to discover the mechanisms and the principal bioactive compounds contributing to HQQFD's protective effects in the treatment of ALI.

An ultra-high performance liquid chromatography-Orbitrap high-resolution mass spectrometry (UHPLC-Orbitrap HRMS) method was employed to characterize the chemical profile in HQQFD and xenobiotics (prototypes and metabolites) in rat lung tissue. Based on prototypes identified, a symptom-guided pharmacological networks of ALI were performed. Molecular docking and extensive literature reviews were conducted to validate our findings.

A total of 105 compounds were identified in HQQFD, and a total of 194 HQQFD-related xenobiotics (30 prototypes and 163 metabolites) were detected in rat lung tissue. Based on prototypes identified in rat lung, a symptom-guided pharmacological networks of ALI were constructed, AKT1, TNF, EGFR, MMP2, GSK3B, STAT3, MAPK8, IL-6, CDK2 and TP53 were finally identified as key targets. Subsequently, 11 compounds with protective and therapeutic activity were selected by molecular docking analysis, including genipin 1-gentiobioside, chrysin-6-C-α-L-arabinoside-8-C-β-d-glucoside, scutellarin, chrysin-6-C-β-d-glucoside-8-C-α-L-arabinoside, 6''-O-[(E)-p-coumaroyl] genipin-gentiobioside, apigenin 7-O-glucoside, baicalin, dihydrobaicalin, wogonoside, crocin I, crocetin. Bioinformatics and literature analysis suggested that, baicalin, wogonoside, genipin 1-gentiobioside and crocetin may be the primary active compounds of HQQFD, potentially targeting GSK3B, MAPK8, IL-6, AKT1 and TNF for HQQFD in addressing ALI. The therapeutic effects of HQQFD may be mediated through the IL-17 and PI3K-AKT signaling pathways.

The predominant components of HQQFD against ALI are baicalein, wogonoside, genipin 1-gentiobiosid and crocetin, with the IL-17 and PI3K-AKT pathways playing crucial roles. This study provides a foundational guide for future research and introduces innovative methods for exploring the mechanisms of other drug combinations or TCM formulas.

Network biology is a powerful framework for studying the structure, function, and dynamics of biological systems, offering insights into the balance between health and disease states. The field is seeing rapid progress in all of its aspects: data availability, network synthesis, network analytics, and impactful applications in medicine and drug development. We review the most recent and significant results in network biomedicine, with a focus on the latest data, analytics, software resources, and applications in medicine. We also discuss what in our view are the likely directions of impactful development over the next few years.

For centuries, Traditional Chinese Medicine (TCM) has been a prominent treatment method in China, incorporating acupuncture, herbal remedies, massage, and dietary therapy to promote holistic health and healing. TCM has played a major role in drug discovery, with over 60% of small-molecule drugs approved by the FDA from 1981 to 2019 being derived from natural products. However, TCM modernization faces challenges such as data standardization and the complexity of TCM formulations. The establishment of comprehensive TCM databases has significantly improved the efficiency and accuracy of TCM research, enabling easier access to information on TCM ingredients and encouraging interdisciplinary collaborations. These databases have revolutionized TCM research, facilitating advancements in TCM modernization and patient care. In addition, advancements in AI algorithms and database data quality have accelerated progress in AI for TCM. The application of AI in TCM encompasses a wide range of areas, including herbal screening and new drug discovery, diagnostic and treatment principles, pharmacological mechanisms, network pharmacology, and the incorporation of innovative AI technologies. AI also has the potential to enable personalized medicine by identifying patterns and correlations in patient data, leading to more accurate diagnoses and tailored treatments. The potential benefits of AI for TCM are vast and diverse, promising continued progress and innovation in the field.

Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus. Its blindness rate is high; therefore, finding a reasonable and safe treatment plan to prevent and control DR is crucial. Currently, there are abundant and diverse research results on the treatment of DR by Chinese medicine Traditional Chinese medicine compounds are potentially advantageous for DR prevention and treatment because of its safe and effective therapeutic effects.

To investigate the effects of Buqing granule (BQKL) on DR and its mechanism from a systemic perspective and at the molecular level by combining network pharmacology and in vivo experiments.

This study collected information on the drug targets of BQKL and the therapeutic targets of DR for intersecting target gene analysis and protein-protein interactions (PPI), identified various biological pathways related to DR treatment by BQKL through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, and preliminarily validated the screened core targets by molecular docking. Furthermore, we constructed a diabetic rat model with a high-fat and high-sugar diet and intraperitoneal streptozotocin injection, and administered the appropriate drugs for 12 weeks after the model was successfully induced. Body mass and fasting blood glucose and lipid levels were measured, and pathological changes in retinal tissue were detected by hematoxylin and eosin staining. ELISA was used to detect the oxidative stress index expression in serum and retinal tissue, and immunohistochemistry, real-time quantitative reverse transcription PCR, and western blotting were used to verify the changes in the expression of core targets.

Six potential therapeutic targets of BQKL for DR treatment, including Caspase-3, c-Jun, TP53, AKT1, MAPK1, and MAPK3, were screened using PPI. Enrichment analysis indicated that the MAPK signaling pathway might be the core target pathway of BQKL in DR treatment. Molecular docking prediction indicated that BQKL stably bound to these core targets. In vivo experiments have shown that compared with those in the Control group, rats in the Model group had statistically significant (P < 0.05) severe retinal histopathological damage; elevated blood glucose, lipid, and malondialdehyde (MDA) levels; increased Caspase-3, c-Jun, and TP53 protein expression; and reduced superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) levels, ganglion cell number, AKT1, MAPK1, and MAPK3 protein expression. Compared with the Model group, BQKL group had reduced histopathological retinal damage and the expression of blood glucose and lipids, MDA level, Caspase-3, c-Jun and TP53 proteins were reduced, while the expression of SOD, GSH-Px level, the number of ganglion cells, AKT1, MAPK1, and MAPK3 proteins were elevated. These differences were statistically significant (P < 0.05).

BQKL can delay DR onset and progression by attenuating oxidative stress and inflammatory responses and regulating Caspase-3, c-Jun, TP53, AKT1, MAPK1, and MAPK3 proteins in the MAPK signaling pathway mediates these alterations.

Cardiovascular and cerebrovascular diseases are the leading causes of death worldwide and interact closely with each other. Danhong Injection (DHI) is a widely used preparation for the co-treatment of brain and heart diseases (CTBH). However, the underlying molecular endotype mechanisms of DHI in the CTBH remain unclear.

To elucidate the underlying endotype mechanisms of DHI in the CTBH.

In this study, we proposed a modular-based disease and drug-integrated analysis (MDDIA) strategy for elucidating the systematic CTBH mechanisms of DHI using high-throughput transcriptome-wide sequencing datasets of DHI in the treatment of patients with stable angina pectoris (SAP) and cerebral infarction (CI). First, we identified drug-targeted modules of DHI and disease modules of SAP and CI based on the gene co-expression networks of DHI therapy and the protein-protein interaction networks of diseases. Moreover, module proximity-based topological analyses were applied to screen CTBH co-module pairs and driver genes of DHI. At the same time, the representative driver genes were validated via in vitro experiments on hypoxia/reoxygenation-related cardiomyocytes and neuronal cell lines of H9C2 and HT22.

Seven drug-targeted modules of DHI and three disease modules of SAP and CI were identified by co-expression networks. Five modes of modular relationships between the drug and disease modules were distinguished by module proximity-based topological analyses. Moreover, 13 targeted module pairs and 17 driver genes associated with DHI in the CTBH were also screened. Finally, the representative driver genes AKT1, EDN1, and RHO were validated by in vitro experiments.

This study, based on clinical sequencing data and modular topological analyses, integrated diseases and drug targets. The CTBH mechanism of DHI may involve the altered expression of certain driver genes (SRC, STAT3, EDN1, CYP1A1, RHO, RELA) through various enriched pathways, including the Wnt signaling pathway.

Hepatic diseases pose a significant threat to community health, impacting the quality of life and longevity of millions worldwide. Despite revolutionary advancements in treatment, liver diseases remain a pressing issue, necessitating the development of more effective therapeutic approaches. Here, we conducted a comprehensive multi-omics analysis to investigate the underlying mechanism of Swertiamarin in alleviating hepatic injuries induced by CCl4 in mice. We divided 100 Kunming mice into five groups: RC (control), RM (CCl4), RD (15 mg/Kg Swertiamarin), RZ (30 mg/Kg Swertiamarin), and RG (60 mg/Kg Swertiamarin). Animals in groups RD, RZ, and RG received daily Swertiamarin via gavage, while those in groups RM, RD, RZ, and RG were treated with CCl4 solution intraperitoneally every four days, nine times in total. Our findings revealed that mice in the RM group exhibited slightly lower average weights compared to other groups, along with significantly higher liver weight (p<0.0001) and liver index (p<0.0001). Pathological analysis indicated liver damage characterized by cell degeneration, inflammatory cell infiltration, and hepatic fibrosis in the CCl4-induced group. In contrast, Swertiamarin supplementation mitigated these effects, reducing denatured cells, inflammatory cells, and collagenous fibers in the liver. Serum analysis showed elevated levels of TNF-α (p<0.001), IL-6 (p<0.05), ALT (p<0.001), AST (p<0.0001), MDA (p<0.001), and Hyp (p<0.001) in CCl4-induced animals, along with lower levels of T-AOC (p<0.001), GSH-px (p<0.0001), SOD (p<0.001), and CAT (p<0.01). Microbiome analysis revealed significant differences among groups, with pathogenic taxa such as Arthrinium and Aureobasidium, and probiotic Saccharomyces showing notable variations. Metabolomics analysis identified numerous differentially abundant metabolites, with Swertiamarin-treated animals exhibiting distinct profiles. Our findings highlight the potential of Swertiamarin ameliorating CCl4-induced liver toxicity through modulation of antioxidant capacity, inflammatory response, gut microbiota, and metabolites. These insights may inform the development of novel therapies for liver injury.

Herbal medicines, particularly traditional Chinese medicines (TCMs), are a rich source of natural products with significant therapeutic potential. However, understanding their mechanisms of action is challenging due to the complexity of their multi-ingredient compositions. We introduced Herb-CMap, a multimodal fusion framework leveraging protein-protein interactions and herb-perturbed gene expression signatures. Utilizing a network-based heat diffusion algorithm, Herb-CMap creates a connectivity map linking herb perturbations to their therapeutic targets, thereby facilitating the prioritization of active ingredients. As a case study, we applied Herb-CMap to Suhuang antitussive capsule (Suhuang), a TCM formula used for treating cough variant asthma (CVA). Using in vivo rat models, our analysis established the transcriptomic signatures of Suhuang and identified its key compounds, such as quercetin and luteolin, and their target genes, including IL17A, PIK3CB, PIK3CD, AKT1, and TNF. These drug-target interactions inhibit the IL-17 signaling pathway and deactivate PI3K, AKT, and NF-κB, effectively reducing lung inflammation and alleviating CVA. The study demonstrates the efficacy of Herb-CMap in elucidating the molecular mechanisms of herbal medicines, offering valuable insights for advancing drug discovery in TCM.

Traditional drug screening methods typically focus on a single protein target and exhibit limited efficiency due to the multifactorial nature of most diseases, which result from disturbances within complex networks of protein-protein interactions rather than single gene abnormalities. Addressing this limitation requires a comprehensive drug screening strategy. Network medicine is rooted in systems biology and provides a comprehensive framework for understanding disease mechanisms, prevention, and therapeutic innovations. This approach not only explores the associations between various diseases but also quantifies the relationships between disease genes and drug targets within interactome networks, thus facilitating the prediction of drug-disease relationships and enabling the screening of therapeutic drugs for specific complex diseases. An increasing body of research supports the efficiency and utility of network-based strategies in drug screening. This review highlights the transformative potential of network medicine in virtual therapeutic screening for complex diseases, offering novel insights and a robust foundation for future drug discovery endeavors.